import time
import random
import logging
from typing import Dict, List, Any
import os

# 配置日志
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger('BenchmarkTest')


class HarmonyAppOperation:
    """
    模拟鸿蒙App的操作
    这个类模拟了在鸿蒙App上执行的各种操作，包括页面导航、元素查找、点击等
    """
    
    def __init__(self, operation_name: str, base_delay: float = 0.5):
        """
        初始化操作
        
        Args:
            operation_name: 操作名称
            base_delay: 基础延迟时间（秒）
        """
        self.operation_name = operation_name
        self.base_delay = base_delay
        self.random_factor = 0.3  # 随机延迟因子
    
    def execute(self) -> float:
        """
        执行操作
        
        Returns:
            执行时间（秒）
        """
        # 计算实际延迟时间（包含随机波动）
        actual_delay = self.base_delay + (random.random() - 0.5) * self.base_delay * self.random_factor * 2
        actual_delay = max(0.01, actual_delay)  # 确保延迟时间不为负
        
        # 模拟操作执行
        start_time = time.time()
        time.sleep(actual_delay)  # 模拟操作耗时
        execution_time = time.time() - start_time
        
        logger.debug(f"执行操作 '{self.operation_name}' 耗时: {execution_time:.3f}秒")
        return execution_time


class HarmonyPage:
    """
    模拟鸿蒙App页面
    包含多个页面操作
    """
    
    def __init__(self, page_name: str, operations_count: int = 5):
        """
        初始化页面
        
        Args:
            page_name: 页面名称
            operations_count: 页面包含的操作数量
        """
        self.page_name = page_name
        # 创建页面操作
        self.operations = [
            HarmonyAppOperation(f"{page_name}_operation_{i}", base_delay=0.3 + (i % 5) * 0.2)
            for i in range(operations_count)
        ]
    
    def navigate_to(self) -> float:
        """
        导航到该页面
        
        Returns:
            导航时间（秒）
        """
        # 模拟页面导航时间
        navigate_time = 1.0 + random.random() * 0.5
        time.sleep(navigate_time)
        logger.info(f"导航到页面 '{self.page_name}' 耗时: {navigate_time:.3f}秒")
        return navigate_time
    
    def execute_operations(self, operation_indices: List[int] = None) -> List[float]:
        """
        执行页面上的操作
        
        Args:
            operation_indices: 要执行的操作索引列表，如果为None则执行所有操作
            
        Returns:
            各操作的执行时间列表
        """
        if operation_indices is None:
            operation_indices = list(range(len(self.operations)))
        
        execution_times = []
        for idx in operation_indices:
            if 0 <= idx < len(self.operations):
                op_time = self.operations[idx].execute()
                execution_times.append(op_time)
        
        return execution_times


class HarmonyTestSuite:
    """
    鸿蒙App测试套件
    模拟传统的串行测试执行方式
    """
    
    def __init__(self, suite_name: str, pages_count: int = 4, operations_per_page: int = 5):
        """
        初始化测试套件
        
        Args:
            suite_name: 测试套件名称
            pages_count: 页面数量
            operations_per_page: 每页操作数量
        """
        self.suite_name = suite_name
        # 创建测试页面
        self.pages = [
            HarmonyPage(f"Page_{i}", operations_per_page)
            for i in range(pages_count)
        ]
        
        self.total_tests = 0
        self.passed_tests = 0
        self.failed_tests = 0
        self.skipped_tests = 0
        self.execution_time = 0.0
        
        logger.info(f"创建测试套件: {suite_name}, 包含 {len(self.pages)} 个页面")
    
    def run(self) -> Dict[str, Any]:
        """
        运行测试套件（模拟传统串行执行）
        
        Returns:
            测试结果
        """
        logger.info(f"开始运行测试套件: {self.suite_name}")
        start_time = time.time()
        
        # 重置测试统计
        self.total_tests = 0
        self.passed_tests = 0
        self.failed_tests = 0
        self.skipped_tests = 0
        
        # 串行执行每个页面的测试
        page_results = []
        for page in self.pages:
            page_result = self._run_page_tests(page)
            page_results.append(page_result)
            
            # 更新统计信息
            self.total_tests += page_result['total_tests']
            self.passed_tests += page_result['passed_tests']
            self.failed_tests += page_result['failed_tests']
            self.skipped_tests += page_result['skipped_tests']
        
        self.execution_time = time.time() - start_time
        logger.info(f"测试套件 {self.suite_name} 执行完成，总耗时: {self.execution_time:.3f}秒")
        
        return {
            'suite_name': self.suite_name,
            'total_tests': self.total_tests,
            'passed_tests': self.passed_tests,
            'failed_tests': self.failed_tests,
            'skipped_tests': self.skipped_tests,
            'total_execution_time': self.execution_time,
            'page_results': page_results,
            'execution_mode': 'serial'  # 传统串行执行
        }
    
    def _run_page_tests(self, page: HarmonyPage) -> Dict[str, Any]:
        """
        运行单个页面的测试
        
        Args:
            page: HarmonyPage实例
            
        Returns:
            页面测试结果
        """
        logger.info(f"开始测试页面: {page.page_name}")
        page_start_time = time.time()
        
        # 导航到页面（模拟非智能等待）
        navigate_time = page.navigate_to()
        
        # 执行页面上的所有操作
        operation_times = page.execute_operations()
        
        # 模拟随机的测试失败
        total_operations = len(operation_times)
        passed_operations = sum(1 for _ in range(total_operations) if random.random() > 0.1)  # 90%通过率
        failed_operations = total_operations - passed_operations
        
        page_execution_time = time.time() - page_start_time
        
        logger.info(f"页面 {page.page_name} 测试完成，执行了 {total_operations} 个操作，通过 {passed_operations} 个，失败 {failed_operations} 个")
        
        return {
            'page_name': page.page_name,
            'total_tests': total_operations,
            'passed_tests': passed_operations,
            'failed_tests': failed_operations,
            'skipped_tests': 0,
            'navigate_time': navigate_time,
            'operation_times': operation_times,
            'total_time': page_execution_time
        }


def run_benchmark_test(pages_count: int = 4, 
                      operations_per_page: int = 5,
                      iterations: int = 3) -> Dict[str, Any]:
    """
    运行基准测试，用于测量原始性能
    
    Args:
        pages_count: 页面数量
        operations_per_page: 每页操作数量
        iterations: 测试迭代次数
        
    Returns:
        基准测试结果
    """
    logger.info(f"开始执行基准测试，页面数: {pages_count}, 每页操作数: {operations_per_page}, 迭代次数: {iterations}")
    
    all_iterations_results = []
    total_execution_time = 0.0
    
    # 执行多次迭代以获得平均性能
    for i in range(iterations):
        logger.info(f"执行迭代 {i+1}/{iterations}")
        
        # 创建测试套件
        test_suite = HarmonyTestSuite(f"Benchmark_Suite_Iteration_{i+1}", 
                                     pages_count=pages_count, 
                                     operations_per_page=operations_per_page)
        
        # 运行测试
        iteration_result = test_suite.run()
        all_iterations_results.append(iteration_result)
        total_execution_time += iteration_result['total_execution_time']
    
    # 计算平均执行时间
    avg_execution_time = total_execution_time / iterations
    
    # 汇总测试结果
    total_tests = sum(r['total_tests'] for r in all_iterations_results)
    total_passed = sum(r['passed_tests'] for r in all_iterations_results)
    total_failed = sum(r['failed_tests'] for r in all_iterations_results)
    total_skipped = sum(r['skipped_tests'] for r in all_iterations_results)
    
    # 计算资源使用估计（模拟数据，实际应该由系统监控）
    estimated_cpu_usage = 45.0 + random.uniform(-5.0, 5.0)  # 模拟CPU使用率
    estimated_memory_usage = 150.0 + random.uniform(-20.0, 20.0)  # 模拟内存使用（MB）
    
    benchmark_results = {
        'test_type': 'benchmark',
        'pages_count': pages_count,
        'operations_per_page': operations_per_page,
        'iterations': iterations,
        'total_tests': total_tests,
        'passed_tests': total_passed,
        'failed_tests': total_failed,
        'skipped_tests': total_skipped,
        'total_execution_time': total_execution_time,
        'average_execution_time': avg_execution_time,
        'iteration_results': all_iterations_results,
        'execution_mode': 'serial',
        'estimated_resources': {
            'average_cpu_usage_percent': estimated_cpu_usage,
            'average_memory_usage_mb': estimated_memory_usage
        },
        'timestamp': time.strftime('%Y-%m-%d %H:%M:%S')
    }
    
    logger.info(f"基准测试完成，总执行时间: {total_execution_time:.3f}秒, 平均执行时间: {avg_execution_time:.3f}秒")
    
    # 保存基准测试结果
    save_benchmark_results(benchmark_results)
    
    return benchmark_results


def save_benchmark_results(results: Dict[str, Any]):
    """
    保存基准测试结果到文件
    
    Args:
        results: 测试结果
    """
    import json
    
    # 确保结果目录存在
    results_dir = './results'
    os.makedirs(results_dir, exist_ok=True)
    
    # 生成文件名
    timestamp = time.strftime('%Y%m%d_%H%M%S')
    filename = f"benchmark_results_{timestamp}.json"
    filepath = os.path.join(results_dir, filename)
    
    try:
        with open(filepath, 'w', encoding='utf-8') as f:
            json.dump(results, f, indent=2, ensure_ascii=False)
        logger.info(f"基准测试结果已保存到: {filepath}")
    except Exception as e:
        logger.error(f"保存基准测试结果失败: {str(e)}")


if __name__ == "__main__":
    # 运行默认的基准测试
    benchmark_results = run_benchmark_test(
        pages_count=5,          # 5个页面
        operations_per_page=6,  # 每页6个操作
        iterations=3            # 运行3次取平均
    )
    
    # 打印关键结果
    print("\n基准测试结果摘要:")
    print(f"总测试用例: {benchmark_results['total_tests']}")
    print(f"通过测试: {benchmark_results['passed_tests']}")
    print(f"失败测试: {benchmark_results['failed_tests']}")
    print(f"总执行时间: {benchmark_results['total_execution_time']:.3f}秒")
    print(f"平均执行时间: {benchmark_results['average_execution_time']:.3f}秒")
    print(f"执行模式: {benchmark_results['execution_mode']}")
    print(f"估计CPU使用率: {benchmark_results['estimated_resources']['average_cpu_usage_percent']:.1f}%")
    print(f"估计内存使用: {benchmark_results['estimated_resources']['average_memory_usage_mb']:.1f} MB")